基于Mindlin理论Winkler地基参数的Kalman滤波识别

提出了Winkler地基参数的Kalman滤波识别方法。引入Mindlin理论后,推导了Winkler地基上板的控制微分方程。利用Fourier变换,推求了Winkler地基上简支板的Fourier闭式解。推导了Winkler地基参数的Kalman滤波方程,研究了Winkler地基参数的Kalman滤波识别的具体计算步骤。研究表明,运用Kalman滤波理论进行Winkler地基参数的识别,能有效地估计Winkler地基参数;Winkler地基参数的滤波收敛速度和精度受地基参数初始值选取和位移实测资料的影响,且Kalman滤波理论也可用于其他地基模型地基参数的识别。     

多传感器观测下带乘性噪声系统的逆向滤波与反褶积融合算法

针对多传感器观测环境下带乘性噪声系统的逆向最优滤波与反褶积融合估计问题 ,本文提出了 1种基于极大似然准则的最优融合算法。该算法中各单传感器间并行计算 ,并且融合中心与单传感器处理中心间无反向通讯 ,因而执行效率较高。仿真表明 ,该融合算法产生的逆向滤波与反褶积比单传感器处理结果有较明显提高     

Waveform Shaping of Sonar Transducers for Improving the Vertical Resolution in Sub-bottom Sediments Profiling

Vertical resolution is of fundamental importance in sonar exploration and is directly related to the duration of the acoustic pulse generated by the transducer. The shorter the radiated pulse, the higher the vertical resolution. Many sub-bottom profiling sonar systems use piezoelectric transducers because they are reversible and well understood. Piezoelectric projectors are normally resonant transducers, which are intrinsically narrowband. A piezoelectric transducer is usually driven by a tone-burst. However, it is possible to use Fourier techniques to find a pre-compensated electrical driving function so that the transducer radiates a prescribed wider band acoustic waveform. This technique can be applied to synthesize zero-phase cosine-magnitude, Gaussian, and bionic pulses, with a conventional sandwich transducer. Zero-phase cosine-magnitude waveforms provide minimum length pulses (and therefore maximum resolution) within a prescribed frequency band.The aim of this paper is to illustrate the synthesis of wideband acoustic pulses using an underwater piezoelectric projector. The conventional acoustic waveform radiated when a Tonpiltz transducer is transiently excited using a “click” and allows its frequency response function to be measured. This function is used to design the electrical signal which then drives the transducer so that it radiates the shortest pulse compatible with its mechanical response. The significant resolution enhancement of the waveform shaping process is illustrated by its application to a sediment wedge model.     

小波气候突变的检测--应用范围及应注意的问题

气候突变及其检测是气候变化研究的一个重要方面。气候突变的表现多种多样,目前也有许多检测气候突变的方法,但这些方法能否准确地检测出气候突变现象,他们的适用范围如何,是一个值得注意的问题。研究表明,尽管小波分析方法在检测序列突变方面具有严格的数学意义,但因为其检测到的是序列的均值突变,因此,在应用于气候突变的检测方面应该特别注意,数学上的严格并不等同于气候意义上的严格。因为某些情况下有些突变点并没有一定的气候意义。     

珠江三角洲网河区水位变化趋势研究

根据珠江三角洲网河区29个验潮站的实测验潮记录,应用傅氏变换与最平滤波器串联的方法来消除月均序列的周期波动对确定水位变化趋势的影响,由低通序列一元线性回归分析确定各站水位的变化趋势;结果表明,周期波动对确定海平面变化趋势的影响是显著的.应用经验正交函数(EOF)对网河区的水位变化场进行分解,由相互独立的时间函数和空间特征函数表征网河区区域的水位变化特征;应用时间特征函数计算区域水位的平均变化率为0.02mm/a.根据验潮站的水位变化趋势,探讨网河区水位变化与河床冲淤的关系.     

基于子波分析的悬浮物散射信号特征提取实验研究

概述了应用子波分析对悬浮物测量中的声散射信号进行特征提取的方法 ,并对声散射信号识别的研究进行了探讨。对实测数据的实验取得了较好的结果     

水下智能潜器的神经网络运动控制

本文介绍一种基于神经网络的水下智能潜器的运动控制方法，该方法通过在线学习，融控制与滤波为一体。计算机仿真与水池实验验证表明，该方法的控制与滤波性能良好，对环境的学习与适应能力强。该方法事实上可用于一般动力系统的控制。     

一种基于BP算法学习的小波神经网络

为发展 Szu的基于信号表示的小波神经网络 ,提出一种多输入多输出的小波网络模型 ,网络隐层采用框架小波函数、输出层采用 Sigmoid激励函数 ,并选用“熵误差函数”以加速网络的学习速度。奇偶判别和混沌时间序列预测例子的实验结果表明了它具有良好的函数逼近能力和推广能力 ,收敛速度和均方误差均优于相同结构的多层感知器模型。     

Multifractal filtering method for extraction of ocean from remotely sensed imagery

Traditional methods of extracting the ocean wave eddy information from remotely sensed imagery mainly use the edge detection technology such as Canny and Hough operators. However, due to the complexities of ocean eddies and image itself, it is sometimes difficult to successfully detect ocean eddies using these methods. A mnltifractal filtering technology is proposed for extraction of ocean eddies and demonstrated using NASA MODIS, SeaWiFS and NOAA satellite data set in the typical area, such as ocean west boundary current. Results showed that the new method has a superior performance over the traditional methods.     

A novel technique in analyzing non-linear wave-wave interaction

During wave growth non-linear wave–wave interactions cause transfer of some wave energy from lower to higher wave periods as the spectrum grows. Wavelet bicoherence, which is a new technique in the analysis of wind–wave and wave–wave interactions, is used to analyze non-linear wave–wave interactions. A selected record of wind wave that contains the maximum wave height observed during 6 h of wave generation is divided into five segments and wavelet bicoherence is computed for the whole record, and for all divided segments. The study shows that the non-linear wave–wave interaction occurs at different bicoherence levels and these levels are different from one segment to another due to the non-stationarity feature of the examined data set.